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In this note we give a probabilistic proof of the existence of an n-vertex graph Gn, n=1, 2, [ctdot ], such that, for some constant c>0, the edges of Gn cannot be covered by n−c log n complete bipartite subgraphs of Gn. This result improves a previous bound due to F. R. K. Chung and is the best possible up to a constant.
We show that an old but not well-known lower bound for the crossing number of a graph yields short proofs for a number of bounds in discrete plane geometry which were considered hard before: the number of incidences among points and lines, the maximum number of unit distances among n points, the minimum number of distinct distances among n points.
Suppose that [Cscr]={cij[ratio ]i, j[ges ]1} is a collection of i.i.d. nonnegative continuous random variables and suppose T is a rooted, directed tree on vertices labelled 1,2,[ctdot ],n. Then the ‘cost’ of T is defined to be c(T)=[sum ](i,j)∈Tcij, where (i, j) denotes the directed edge from i to j in the tree T. Let Tn denote the ‘optimal’ tree, i.e. c(Tn)=min{c(T)[ratio ]T is a directed, rooted tree in with n vertices}. We establish general conditions on the asymptotic behaviour of the moments of the order statistics of the variables c11, c12, [ctdot ], cin which guarantee the existence of sequences {an}, {bn}, and {dn} such that b−1n(c(Tn)−an)→N(0, 1) in distribution, d−1nc(Tn)→1 in probability, and d−1nE(c(Tn))→1 as n→∞, and we explicitly determine these sequences. The proofs of the main results rely upon the properties of general random mappings of the set {1, 2, [ctdot ], n} into itself. Our results complement and extend those obtained by McDiarmid [9] for optimal branchings in a complete directed graph.
For a graph G=(V, E) on n vertices, where 3 divides n, a triangle factor is a subgraph of G, consisting of n/3 vertex disjoint triangles (complete graphs on three vertices). We discuss the problem of determining the minimal probability p=p(n), for which a random graph G∈[Gscr](n, p) contains almost surely a triangle factor. This problem (in a more general setting) has been studied by Alon and Yuster and by Ruciński, their approach implies p=O((log n/n)1/2). Our main result is that p=O(n)−3/5) already suffices. The proof is based on a multiple use of the Janson inequality. Our approach can be extended to improve known results about the threshold for the existence of an H-factor in [Gscr](n, p) for various graphs H.
Let Q be a stochastic matrix and I be the identity matrix. We show by a direct combinatorial approach that the coefficients of the characteristic polynomial of the matrix I−Q are log-concave. We use this fact to prove a new bound for the second-largest eigenvalue of Q.
Thomassen [6] conjectured that if I is a set of k−1 arcs in a k-strong tournament T, then T−I has a Hamiltonian cycle. This conjecture was proved by Fraisse and Thomassen [3]. We prove the following stronger result. Let T=(V, A) be a k-strong tournament on n vertices and let X1, X2, [ctdot ], Xl be a partition of the vertex set V of T such that [mid ]X1[mid ][les ][mid ]X2[mid ][les ][ctdot ][les ][mid ]Xl[mid ]. If k[ges ][sum ]l−1i=1[lfloor][mid ]Xi[mid ]/2[rfloor]+[mid ]Xl[mid ], then T−∪li=1{xy∈A[ratio ]x, y∈Xi} has a Hamiltonian cycle. The bound on k is sharp.
Let D1 and D2 be two dice with k and l integer faces, respectively, where k and l are two positive integers. The game Gn consists of tossing each die n times and summing the resulting faces. The die with the higher total wins the game. We examine the question of which die wins game Gn more often, for large values of n. We also give an example of a set of three dice which is non-transitive in game Gn for infinitely many values of n.
We show that there are almost surely only finitely many times at which there are at least four ‘tied’ favourite edges for a simple random walk. This (partially) answers a question of Erdős and Révész.
In this paper we show that the list chromatic index of the complete graph Kn is at most n. This proves the list-chromatic conjecture for complete graphs of odd order. We also prove the asymptotic result that for a simple graph with maximum degree d the list chromatic index exceeds d by at most [Oscr](d2/3√log d).
The previous chapter was devoted to constructing objects by transfinite induction. A typical scheme for such constructions was a diagonalization argument like the following. To find a subset S of a set X concerning a family P = {Pα : α < κ} we chose S = {xξ ∈ X : ξ < κ} by picking each xξ to take care of a set Pξ. But what can we do if the cardinal κ is too big compared to the freedom of choice of the xξs; for example, if the set X has cardinality less than κ?
There is no absolute answer to this question. In some cases you can do nothing. For example, if you try to construct a subset S of ω different from every set from the family P(ω) = {Bξ: ξ < c}, then you are obviously condemned to failure. The inductive construction does not work, since you would have to take care of continuum many conditions, having the freedom to choose only count ably many points for S.
In some other cases you can reduce a family P to the appropriate size. This was done, for example, in Theorem 6.3.7 (on the existence of Bernstein sets) in which we constructed a nonmeasurable subset B of ℝn: The natural family P - ℒ of cardinality 2c was replaced by the family P0 = {Pξ: ξ < c} of all perfect subsets of ℝn.
We first review some notions and facts about continuous representations of
in a locally complete topological vector space V. In fact, all we need is the representation by right translations of G in C∞(G), L2(G), C∞(H\G), or L2(H\G) (H closed unimodular subgroup, mainly F). Much of this has been encountered earlier, implicitly or explicitly. All this is valid in a much more general framework (see e.g. [7]).
A continuous representation (π, V) of G into V is a homomorphism of G into the group of automorphisms of V that is continuous; in other words, the map (g, v) ↦ π(g).v is a continuous map of G × V into V. If V is a Hilbert space then it is said to be i>unitary if π (g) (g ∈ G) leaves the scalar product of V invariant. Then the operator norm ∥π(g)∥ is uniformly bounded (by 1), and it is known that continuity already follows from separate continuity:
(1) for every v ∈ V, the map g ↦ π(g).v of G into V is continuous (see e.g. [7, §3] or [10, §VIII.1]).
The assumption “locally complete” is made to ensure that if α ∈ Cc(G) then ∫G α(x)π(x).v dx converges to an element of V. More generally, ∫ µ(x)π(x).v converges if µ is a compactly supported measure on G (see an important example in 14.4).
This chapter is designed to help the reader to master the technique of recursive definitions. Thus, most of the examples presented will involve constructions by transfinite induction.
Measurable and nonmeasurable functions
Let B be a σ-algebra on ℝn. A function f: ℝ → ℝ is said to be a B-measurable function if f-1(U) ∈ B for every open set U ⊂ ℝ. Notice that if f is B-measurable then f-1(B) ∈ B for every Borel set B ⊂ ℝ. This is the case since the family {B ⊂ ℝ: f-1(B) ∈ B} is a σ-algebra containing all open sets.
We will use this notion mainly for the σ-algebras of Borel, Lebesguemeasurable, and Baire subsets of ℝn, respectively. In each of these cases B-measurable functions will be termed, respectively, as Borel functions (or Borel-measurable functions), measurable functions (or Lebesgue-measurable functions), and Baire functions (or Baire-measurable functions). Clearly, every continuous function is Borel-measurable and every Borel-measurable function is measurable and Baire.
A function f: ℝn → ℝ is non-Borel (or non-Borel-measurable) if it is not Borel. Similarly, we define non-Baire (-measurable) functions and non-(Lebesgue-)measurable functions.
Also recall that the characteristic function χA of a subset A of a set X is defined by putting χA(x) = 1 if x ∈ A and χA(x) = 0 for x ∈ X \ A.
The first theorem is a corollary to Theorems 6.3.7 and 6.3.8.